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Noise-tolerant Image Restoration with Similarity-learned Fuzzy Association Memory
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퍼지연상메모리를 이용한 잡음 내성 이미지 복원

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Type
Academic journal
Author
Choong Shik Park (U1 University)
Journal
The Korean Society Of Computer And Information Journal of the Korea Society of Computer and Information Vol.25 No.3(Wn.192) KCI Accredited Journals
Published
2020.3
Pages
51 - 55 (5page)

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Noise-tolerant Image Restoration with Similarity-learned Fuzzy Association Memory
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Abstract· Keywords

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In this paper, an improved FAM is proposed by adopting similarity learning in the existing FAM(Fuzzy Associative Memory) used in image restoration. Image restoration refers to the recovery of the latent clean image from its noise-corrupted version. In serious application like face recognition, this process should be noise-tolerant, robust, fast, and scalable. The existing FAM is a simple single layered neural network that can be applied to this domain with its robust fuzzy control but has low capacity problem in real world applications. That similarity measure is implied to the connection strength of the FAM structure to minimize the root mean square error between the recovered and the original image. The efficacy of the proposed algorithm is verified with significant low error magnitude from random noise in our experiment.
#Image Restoration #Fuzzy Associative Memory #Similarity Learning. Similarity Measure #이미지 복원 #퍼지 연상 메모리 #유사성 학습 #유사성 측정

Contents

[Abstract]
[요약]
I. Introduction
II. Improved Fuzzy Associative Memory
III. Result And Discussion
IV. Conclusions
REFERENCES

References (8)

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B. Kosko / 1992 / Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence / Prentice Hall google schola M. T. Hagan / 1996 / Neural Network Design / PWS Publishing Company google schola T. Yamaguchi / 2003 / Intention Recognition Using Case-Base Learning in Human Vehicle / Proceedings of ISIS :110~113 google schola Peter Sussner / 2006 / Implicative Fuzzy Associative Memories / IEEE Transactions on Fuzzy Systems 14(6):793~807 Crossref The Duy Bui / 2015 / Improving learning rule for fuzzy associative memory with combination of content and association / Neurocomputing 149:59~64 Crossref

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